A finite mixture modelling perspective for combining experts’ opinions with an application to quantile-based risk measures

Makariou, Despoina ORCID: 0000-0002-9001-2122, Barrieu, Pauline ORCID: 0000-0001-9473-263X and Tzougas, George (2021) A finite mixture modelling perspective for combining experts’ opinions with an application to quantile-based risk measures. Risks, 9 (6). ISSN 2227-9091

Text (risks-09-00115-v2) - Published Version Available under License Creative Commons Attribution. Download (649kB)

• Author
• Author

Abstract

The key purpose of this paper is to present an alternative viewpoint for combining expert opinions based on finite mixture models. Moreover, we consider that the components of the mixture are not necessarily assumed to be from the same parametric family. This approach can enable the agent to make informed decisions about the uncertain quantity of interest in a flexible manner that accounts for multiple sources of heterogeneity involved in the opinions expressed by the experts in terms of the parametric family, the parameters of each component density, and also the mixing weights. Finally, the proposed models are employed for numerically computing quantile-based risk measures in a collective decision making context.

Item Type:	Article
Official URL:	https://www.mdpi.com/journal/risks
Additional Information:	© 2021 The Authors
Divisions:	Statistics
Subjects:	H Social Sciences > HA Statistics
Date Deposited:	03 Jun 2021 15:51
Last Modified:	26 Oct 2024 01:12
URI:	http://eprints.lse.ac.uk/id/eprint/110763

Actions (login required)

View Item